Energy optimisation using analytics and coordination, the example of lifts

This paper focuses on energy optimisation in the context of lifts. Modern lifts embed batteries that are so far used only in emergency. We propose a multi-level optimisation strategy to reduce the electricity bill by combining harvesting, the grid and energy stored in batteries. The strategy combines several analytic components (forecaster, optimisers), modelled/measured variables, and is used by the control system. A coordination middleware enables the cooperation between the components embedded in the lift or located in the cloud, thus requiring communication through firewalls of different companies. Early results are presented. They illustrate new features for improving energy efficiency and they demonstrate our capacity to build such an optimisation architecture in a real environment. Part of the results are simulated to extrapolate the reachable energy gain.